Ingo Riederer

1.1k citations
29 papers · 891 · h-index 17

Impact in

Papers in

Ingo Riederer

28 papers receiving 881 citations

Peers

Ingo Riederer
Comparison fields: 5 of 90
  • Genetics 148
  • Rehabilitation 80
  • Molecular Biology 531
  • Cell Biology 121
  • Immunology and Allergy 42
Replace Francis M. Chen with:
Francis M. Chen Hong Kong
Jolana Turečková Czechia
Suse Dayse Silva-Barbosa Brazil
T. A. Robertson Australia
Anne‐Cécile Rimaniol France
Eko Raharjo Canada
Nena J. Winand United States
Patrizia Pessina United States
Tatiana V. Cohen United States
Alexis R. Demonbreun United States
Ingo Riederer relative to Francis M. Chen Hong Kong Francis M. Chen's profile →
Citations per field
00.5×2.6×
Francis M. Chen · 1×
Citations per year

Countries citing papers authored by Ingo Riederer

Since Specialization
Citations

This map shows the geographic impact of Ingo Riederer's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ingo Riederer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ingo Riederer more than expected).

Fields of papers citing papers by Ingo Riederer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ingo Riederer. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ingo Riederer. The network helps show where Ingo Riederer may publish in the future.

Co-authors

The 25 scholars most cited alongside Ingo Riederer, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ingo Riederer Line = papers co-authored together Ingo Riederer links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009142
2 2012117
3 2009106
4
Myoblast transfer therapy: is there any light at the end of the tunnel?
200561
5 200350
6 201745
7 201141
8 200835
9 198627
10 201824
11 201522
12 201521
13 199720
14 200819
15 202019
16 201517
17 200517
18 201816
19 202016
20 202014

About Ingo Riederer

Ingo Riederer is a scholar working on Molecular Biology, Immunology, Surgery, Epidemiology and Genetics, having authored 29 papers that have together received 891 indexed citations. Recurring topics across this work include Muscle Physiology and Disorders (13 papers), Mesenchymal stem cell research (5 papers), Tissue Engineering and Regenerative Medicine (5 papers), Mosquito-borne diseases and control (3 papers), Signaling Pathways in Disease (3 papers), Cell Adhesion Molecules Research (3 papers), CAR-T cell therapy research (3 papers) and T-cell and B-cell Immunology (3 papers). The work is most often cited by research in Genetics (148 citations), Rehabilitation (80 citations), Molecular Biology (531 citations), Cell Biology (121 citations) and Immunology and Allergy (42 citations). Ingo Riederer has collaborated with scholars based in Brazil, France and United Kingdom. Frequent co-authors include Vincent Mouly, Gillian Butler‐Browne, Wilson Savino, Elisa Négroni, James P. Di Santo, Zehava Uni, Orna Halevy, Suse Dayse Silva-Barbosa, Soraya Chaouch and Ahmed Aamiri. Their work appears in journals such as Molecular Therapy, Frontiers in Immunology, Memórias do Instituto Oswaldo Cruz, Skeletal Muscle and PLoS neglected tropical diseases.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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